ABSTRACT- DATA MANAGEMENT & STATISTICS (DMS) CORE The Data Management and Statistical (DMS) Core supports the NYU Alzheimer's Disease Research Center (ADRC) and its Cores by providing state-of-the-art data and information management and statistical expertise. The DMS Core aims to provide cutting edge research data management (AIM 1), by providing a customized, comprehensive and scalable data acquisition and management platform in REDCap and provide scalable technologies like Tableau for data visualization. The core will maintain unique linkages between the participants and their data captured from other core's activities and from various collaborative/ affiliated studies, including incorporating the global unique identifier (GUID) to streamline data collaborations between centers. DMS will continue its inter core collaboration by, maintaining the database in collaboration; maintaining a dynamic registry; maintaining standardized brain measures in the database; providing informatics and statistical collaboration for the BMS core. The core will continue to provide scalable storage solutions and be the conduit to share data with researchers and collaborators through latest tools and new systems. DMS will also interface with NACC to implement data acquisition forms, submit UDS data in a timely manner and be swiftly handle query resolution. DMS will continue to develop and implement innovative tools to incorporate various data sets including the vast ?-omics? data and also make the tools available to the wider research community through our website and social media. The DMS Core also aims to provide state-of-the-art statistical support (AIM 2) and promote scientific rigor, by providing comprehensive statistical collaboration and consultation to all the Cores at NYU ADRC across the entire spectrum of the translational research process of study design, conduct, analysis, visualization, interpretation, and reporting of clinical, translational, and population-based research. DMS core will develop innovative study designs and new statistical methods to address emerging research directions undertaken by ADRC investigators that include developing new statistical models and methods to deal with latent heterogeneities in ADRD, effective risk prediction models with variable selection, novel machine learning methods for high dimensional data, and open platform computing algorithms and R packages. Finally, the DMS Core mentors center affiliated young investigators and trainees in addition to promoting scientific rigor with extensive statistical support, facilitating collaboration and optimizing resources with cutting edge data management, and magnifying the impact of findings by promoting reproducible research and data sharing.